The Lithium ion battery is widely used in most of the battery powered electronics and automotive products like mobile phones, laptop, wall watch, calculator and other. The Battery provides power to devices with the facility of movability. On the other hand, it also provides power backup to devices. The Battery State of charge (SOC) and state of health (SOH) are the key terms by which the available charge and its life span can be estimated. In this paper, SOC is estimated using a backpropagation neural network with 3 inputs namely, voltage, current, and temperature of the battery. Coulomb counting method is used to find the new or remaining capacity of the battery which will notify about its SOH. The whole setup is implemented in PIC16F877A with the voltage, current and temperature sensors.
In any service-providing organization, it is necessary to answer current or future customer’s questions for their information and for maintaining good relationship with the customers. These organizations usually have call centers with hundreds and thousands of employees to give replies to customers through chat (i.e. text) or phone calls. These kind of traditional systems need large number of employees which eventually increases the overall expenditure and manpower requirement of that organization. This paper is aimed at minimizing the manpower requirement i.e. decreasing the number of employees by implementing a chat service. This concept of chatbot has been proposed for implementation in College Website that will automatically reply to the queries of stakeholders like students, parents, etc. without any human interaction. For implementation of chatbot sequence to sequence model is used which is a deep neural network
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